Variable descriptions

glimpse(nri)
## Rows: 50
## Columns: 76
## $ OID_       <dbl> 47346, 47471, 48413, 48503, 48508, 48509, 48904, 48905, 489…
## $ NRI_ID     <chr> "T51065020101", "T51065020300", "T51003010201", "T510790301…
## $ STATE      <chr> "Virginia", "Virginia", "Virginia", "Virginia", "Virginia",…
## $ STATEABBRV <chr> "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA",…
## $ STATEFIPS  <dbl> 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51,…
## $ COUNTY     <chr> "Fluvanna", "Fluvanna", "Albemarle", "Greene", "Albemarle",…
## $ COUNTYTYPE <chr> "County", "County", "County", "County", "County", "County",…
## $ COUNTYFIPS <chr> "065", "065", "003", "079", "003", "003", "003", "003", "07…
## $ STCOFIPS   <dbl> 51065, 51065, 51003, 51079, 51003, 51003, 51003, 51003, 510…
## $ TRACT      <chr> "020101", "020300", "010201", "030102", "010800", "011000",…
## $ TRACTFIPS  <dbl> 51065020101, 51065020300, 51003010201, 51079030102, 5100301…
## $ POPULATION <dbl> 5571, 5311, 4664, 5393, 5325, 6292, 3765, 3738, 9145, 9341,…
## $ BUILDVALUE <dbl> 551401000, 530703000, 589443000, 569304000, 707799000, 1265…
## $ AGRIVALUE  <dbl> 1000124.0179, 2454071.5733, 998608.4291, 2592134.2808, 1253…
## $ AREA       <dbl> 43.2172270, 101.6045726, 27.0136979, 63.8718600, 5.3042504,…
## $ CFLD_EVNTS <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_AFREQ <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_EXPB  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_EXPP  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_EXPPE <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_EXPT  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_HLRB  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_HLRP  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_HLRR  <chr> "Not Applicable", "Not Applicable", "Not Applicable", "Not …
## $ DRGT_EVNTS <dbl> 126, 154, 70, 70, 77, 77, 91, 91, 63, 105, 154, 70, 98, 126…
## $ DRGT_AFREQ <dbl> 7.000000, 8.555556, 3.888889, 3.888889, 4.277778, 4.277778,…
## $ DRGT_EXPB  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ DRGT_EXPP  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ DRGT_EXPPE <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ DRGT_EXPA  <dbl> 611186.8998, 2096304.6178, 898747.5862, 2592134.2808, 12536…
## $ DRGT_EXPT  <dbl> 611186.8998, 2096304.6178, 898747.5862, 2592134.2808, 12536…
## $ DRGT_HLRB  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ DRGT_HLRP  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ DRGT_HLRA  <dbl> 0.003197017, 0.003197017, 0.003222722, 0.004763245, 0.00322…
## $ DRGT_HLRR  <chr> "Very High", "Very High", "Very High", "Very High", "Very H…
## $ HWAV_EVNTS <dbl> 8, 8, 6, 6, 6, 6, 6, 6, 12, 8, 5, 6, 6, 8, 5, 12, 6, 6, 6, …
## $ HWAV_AFREQ <dbl> 0.6589786, 0.6589786, 0.4942339, 0.3947789, 0.4942339, 0.49…
## $ HWAV_EXPB  <dbl> 551400513, 530702957, 589442851, 546678926, 707799000, 1265…
## $ HWAV_EXPP  <dbl> 5570.997, 5311.000, 4663.998, 5231.000, 5325.000, 6291.996,…
## $ HWAV_EXPPE <dbl> 41225376461, 39301398589, 34513586247, 38709396581, 3940500…
## $ HWAV_EXPT  <dbl> 41776776974, 39832101546, 35103029097, 39256075507, 4011279…
## $ HWAV_HLRB  <dbl> 1.169e-12, 1.169e-12, 1.169e-12, 1.169e-12, 1.169e-12, 1.16…
## $ HWAV_HLRP  <dbl> 3.971792e-07, 3.971792e-07, 1.058701e-07, 5.350162e-07, 1.0…
## $ HWAV_HLRR  <chr> "Very Low", "Very Low", "Very Low", "Relatively Low", "Very…
## $ HRCN_EVNTS <dbl> 6, 7, 9, 9, 9, 9, 9, 9, 9, 6, 8, 9, 9, 5, 8, 9, 8, 8, 8, 4,…
## $ HRCN_AFREQ <dbl> 0.06582491, 0.06589680, 0.07046340, 0.07180899, 0.06582491,…
## $ HRCN_EXPB  <dbl> 550733910, 530380270, 589442851, 569303923, 704074505, 1265…
## $ HRCN_EXPP  <dbl> 5564.073, 5307.788, 4663.998, 5393.000, 5312.928, 6291.648,…
## $ HRCN_EXPPE <dbl> 41174136929, 39277633809, 34513586247, 39908196307, 3931566…
## $ HRCN_EXPT  <dbl> 41724870839, 39808014079, 35103029097, 40477500230, 4001973…
## $ HRCN_HLRB  <dbl> 0.0001627591, 0.0001627591, 0.0001627591, 0.0001627591, 0.0…
## $ HRCN_HLRP  <dbl> 1.432476e-06, 1.432476e-06, 1.432476e-06, 1.599039e-06, 1.4…
## $ HRCN_HLRR  <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ RFLD_EVNTS <dbl> 3, 3, 59, 37, 59, 59, 59, 59, 37, 3, 44, 59, 59, 7, 44, 59,…
## $ RFLD_AFREQ <dbl> 0.1363636, 0.1363636, 2.6818182, 1.6818182, 2.6818182, 2.68…
## $ RFLD_EXPB  <dbl> 1649205.9, 3600534.0, 14450941.1, 3620317.5, 699096.0, 2420…
## $ RFLD_EXPP  <dbl> 11.836098, 35.576304, 102.666978, 36.554255, 5.629246, 120.…
## $ RFLD_EXPPE <dbl> 87587125, 263264651, 759735634, 270501484, 41656421, 893340…
## $ RFLD_EXPA  <dbl> 50281.8794, 168074.2006, 44928.6765, 85771.0354, 488.6131, …
## $ RFLD_EXPT  <dbl> 89286613, 267033259, 774231504, 274207572, 42356006, 917627…
## $ RFLD_HLRB  <dbl> 2.251579e-04, 2.251579e-04, 4.212615e-05, 2.905738e-03, 4.2…
## $ RFLD_HLRP  <dbl> 4.003475e-05, 4.003475e-05, 9.587986e-06, 4.040050e-06, 9.5…
## $ RFLD_HLRA  <dbl> 0.009312590, 0.009312590, 0.011180959, 0.009741927, 0.01118…
## $ RFLD_HLRR  <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ SWND_EVNTS <dbl> 369, 368, 390, 396, 368, 369, 369, 368, 397, 369, 363, 369,…
## $ SWND_AFREQ <dbl> 11.53125, 11.52825, 12.20950, 12.40625, 11.53125, 11.53125,…
## $ SWND_EXPB  <dbl> 551401000, 530703000, 589443000, 569304000, 707799000, 1265…
## $ SWND_EXPP  <dbl> 5571, 5311, 4664, 5393, 5325, 6292, 3765, 3738, 9145, 9341,…
## $ SWND_EXPPE <dbl> 41225400000, 39301400000, 34513600000, 39908200000, 3940500…
## $ SWND_EXPA  <dbl> 1000124.0179, 2454071.5733, 998608.4291, 2592134.2808, 1253…
## $ SWND_EXPT  <dbl> 41777801124, 39834557072, 35104041608, 40480096134, 4011292…
## $ SWND_HLRB  <dbl> 8.246272e-06, 8.246272e-06, 2.383243e-06, 7.876500e-06, 2.3…
## $ SWND_HLRP  <dbl> 2.889675e-07, 2.889675e-07, 3.395608e-07, 2.939429e-07, 3.3…
## $ SWND_HLRA  <dbl> 0.0001960432, 0.0001960432, 0.0003132078, 0.0002843516, 0.0…
## $ SWND_HLRR  <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ NRI_VER    <chr> "October 2020", "October 2020", "October 2020", "October 20…

Observations are census tract estimates of…

  • Population, building value, agricultural value within tract, area of tract
  • Natural hazards include: CFLD - coastal flooding, DRGT - drought, HWAV - heat wave, HRCN - hurricane, RFLD - riverine flooding, SWND - strong wind
  • Hazard measures include: EVNTS - number of events in recording period, AFREQ - annualized frequency (# events/# years in recording period)
  • Exposure measures include: EXPB - building value exposure, EXPP - population exposure, EXPE - population equivalence exposure, EXPA - agricultural value exposure
  • Historic loss ratio measures include: HLRB - historic loss ratio for building value, HLRA - historicla loss ratio for agriculture, HLRP - historical loss ratio for population, HLRR - historic loss ratio overall

Summaries

5-number summaries of (non-missing) numeric variables (remove tract identifiers)

nri %>% select(-c(OID_:STATEFIPS, COUNTYTYPE:TRACTFIPS, NRI_VER)) %>% 
  select(where(~is.numeric(.x) && !is.na(.x))) %>% 
  as.data.frame() %>% 
  stargazer(., type = "text", title = "Summary Statistics", digits = 0,
            summary.stat = c("mean", "sd", "min", "median", "max"))
## 
## Summary Statistics
## =====================================================================================
## Statistic       Mean         St. Dev.         Min           Median          Max      
## -------------------------------------------------------------------------------------
## POPULATION     4,694          1,741          1,900          4,382          9,341     
## BUILDVALUE  600,914,960    274,394,213    210,947,000    559,413,000   1,352,245,000 
## AGRIVALUE    1,701,520      2,542,400          0           931,421       13,226,654  
## AREA             43             53             0              18            195      
## DRGT_EVNTS       97             24             63             91            161      
## DRGT_AFREQ       5              1              4             5.1             9       
## DRGT_EXPA    1,372,734      2,012,315          0           596,796       8,841,211   
## DRGT_EXPT    1,372,734      2,012,315          0           596,796       8,841,211   
## DRGT_HLRA        0              0              0              0              0       
## HWAV_EVNTS       7              2              5              6              12      
## HWAV_AFREQ       1              0              0              0              1       
## HWAV_EXPB   594,263,002    268,213,179    210,947,000    549,039,719   1,352,244,990 
## HWAV_EXPP      4,678          1,740          1,900          4,351          9,341     
## HWAV_EXPPE 34,615,220,205 12,878,768,794 14,060,000,000 32,197,399,778 69,123,399,489
## HWAV_EXPT  35,209,483,206 13,089,228,055 14,270,947,000 32,668,421,302 70,475,644,479
## HWAV_HLRB        0              0              0              0              0       
## HWAV_HLRP        0              0              0              0              0       
## HRCN_EVNTS       8              1              4              9              9       
## HRCN_AFREQ       0              0              0              0              0       
## HRCN_EXPB   599,680,668    274,451,546    210,947,000    559,079,443   1,349,737,674 
## HRCN_EXPP      4,689          1,744          1,900          4,382          9,321     
## HRCN_EXPPE 34,695,606,309 12,903,118,962 14,060,000,000 32,426,797,882 68,974,004,894
## HRCN_EXPT  35,295,286,977 13,115,107,535 14,270,947,000 32,941,525,397 70,323,742,568
## HRCN_HLRB        0              0              0              0              0       
## HRCN_HLRP        0              0              0              0              0       
## RFLD_EVNTS       30             25             0              15             59      
## RFLD_AFREQ       1              1              0              1              3       
## RFLD_EXPB    13,388,752     13,835,303         0          8,427,838      54,305,747  
## RFLD_EXPP        89             93             0              62            416      
## RFLD_EXPPE  661,263,174    690,685,745         0         460,988,960   3,081,542,905 
## RFLD_EXPA     153,755        313,700           0            38,504       1,708,403   
## RFLD_EXPT   674,805,682    703,954,174         0         469,495,154   3,137,557,055 
## RFLD_HLRB        0              0              0              0              0       
## RFLD_HLRP        0              0              0              0              0       
## RFLD_HLRA        0              0              0              0              0       
## SWND_EVNTS      369             9             354            368            397      
## SWND_AFREQ       12             0              11             12             12      
## SWND_EXPB   600,914,960    274,394,213    210,947,000    559,413,000   1,352,245,000 
## SWND_EXPP      4,694          1,741          1,900          4,382          9,341     
## SWND_EXPPE 34,737,376,000 12,882,414,388 14,060,000,000 32,426,800,000 69,123,400,000
## SWND_EXPA    1,701,520      2,542,400          0           931,421       13,226,654  
## SWND_EXPT  35,339,992,480 13,094,503,181 14,270,950,433 32,954,976,874 70,475,710,779
## SWND_HLRB        0              0              0              0              0       
## SWND_HLRP        0              0              0              0              0       
## SWND_HLRA        0              0              0              0              0       
## -------------------------------------------------------------------------------------

Summaries of (non-missing) character variables (remove tract identifiers)

nri %>% select(-c(OID_:STATEFIPS, COUNTYTYPE:TRACTFIPS, NRI_VER)) %>% 
  select(where (~is.character(.x))) %>% map(tabyl)
## $COUNTY
##          .x[[i]]  n percent
##        Albemarle 22    0.44
##  Charlottesville 12    0.24
##         Fluvanna  4    0.08
##           Greene  3    0.06
##           Louisa  6    0.12
##           Nelson  3    0.06
## 
## $CFLD_HLRR
##         .x[[i]]  n percent
##  Not Applicable 50       1
## 
## $DRGT_HLRR
##              .x[[i]]  n percent
##            No Rating 12    0.24
##  Relatively Moderate  9    0.18
##            Very High 29    0.58
## 
## $HWAV_HLRR
##         .x[[i]]  n percent
##  Relatively Low  3    0.06
##        Very Low 47    0.94
## 
## $HRCN_HLRR
##   .x[[i]]  n percent
##  Very Low 50       1
## 
## $RFLD_HLRR
##    .x[[i]]  n percent
##  No Rating  8    0.16
##   Very Low 42    0.84
## 
## $SWND_HLRR
##   .x[[i]]  n percent
##  Very Low 50       1

Visual distribution

Via a grouped series of histograms

Tract assets

nri %>% select(TRACTFIPS:AREA) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  geom_histogram() + 
  facet_wrap(~measure, scales = "free")

Tract hazards: Drought

nri %>% select(contains("DRGT"), TRACTFIPS) %>% select(-contains("HLRR")) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  geom_histogram() + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  facet_wrap(~measure, scales = "free")

Tract hazards: Heat Wave

nri %>% select(contains("HWAV"), TRACTFIPS) %>% select(-contains("HLRR")) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  geom_histogram() + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  facet_wrap(~measure, scales = "free")

Tract hazards: Hurricane

nri %>% select(contains("HRCN"), TRACTFIPS) %>% select(-contains("HLRR")) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  geom_histogram() + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  facet_wrap(~measure, scales = "free")

Tract hazards: Riverine Flooding

nri %>% select(contains("RFLD"), TRACTFIPS) %>% select(-contains("HLRR")) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  geom_histogram() + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  facet_wrap(~measure, scales = "free")

Tract hazards: Strong Wind

nri %>% select(contains("SWND"), TRACTFIPS) %>% select(-contains("HLRR")) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  geom_histogram() + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  facet_wrap(~measure, scales = "free")

Maps

Droughts

# DRGT
pal <- colorNumeric("plasma", reverse = TRUE, domain = cville_nri$DRGT_AFREQ) # viridis

leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons(data = cville_nri,
              fillColor = ~pal(DRGT_AFREQ),
              weight = 1,
              opacity = 1,
              color = "white", 
              fillOpacity = 0.6,
              highlight = highlightOptions(
                weight = 2,
                fillOpacity = 0.8,
                bringToFront = T
              ),
              popup = paste0("Tract Number: ", cville_nri$NAME, "<br>",
                             "Ann. Freq.: ", round(cville_nri$DRGT_AFREQ, 2))
  ) %>% 
  addLegend("bottomright", pal = pal, values = cville_nri$DRGT_AFREQ, 
            title = "Drought-#/year", opacity = 0.7)

Heat Wave

# HWAV
pal <- colorNumeric("plasma", reverse = TRUE, domain = cville_nri$HWAV_AFREQ) # viridis

leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons(data = cville_nri,
              fillColor = ~pal(HWAV_AFREQ),
              weight = 1,
              opacity = 1,
              color = "white", 
              fillOpacity = 0.6,
              highlight = highlightOptions(
                weight = 2,
                fillOpacity = 0.8,
                bringToFront = T
              ),
              popup = paste0("Tract Number: ", cville_nri$NAME, "<br>",
                             "Ann. Freq.: ", round(cville_nri$HWAV_AFREQ, 2))
  ) %>% 
  addLegend("bottomright", pal = pal, values = cville_nri$HWAV_AFREQ, 
            title = "Heat Wave-#/year", opacity = 0.7)

Hurricane

# HRCN
pal <- colorNumeric("plasma", reverse = TRUE, domain = cville_nri$HRCN_AFREQ) # viridis

leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons(data = cville_nri,
              fillColor = ~pal(HRCN_AFREQ),
              weight = 1,
              opacity = 1,
              color = "white", 
              fillOpacity = 0.6,
              highlight = highlightOptions(
                weight = 2,
                fillOpacity = 0.8,
                bringToFront = T
              ),
              popup = paste0("Tract Number: ", cville_nri$NAME, "<br>",
                             "Ann. Freq.: ", round(cville_nri$HRCN_AFREQ, 2))
  ) %>% 
  addLegend("bottomright", pal = pal, values = cville_nri$HRCN_AFREQ, 
            title = "Hurricane-#/year", opacity = 0.7)

Riverine Flooding

# RFLD
pal <- colorNumeric("plasma", reverse = TRUE, domain = cville_nri$RFLD_AFREQ) # viridis

leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons(data = cville_nri,
              fillColor = ~pal(RFLD_AFREQ),
              weight = 1,
              opacity = 1,
              color = "white", 
              fillOpacity = 0.6,
              highlight = highlightOptions(
                weight = 2,
                fillOpacity = 0.8,
                bringToFront = T
              ),
              popup = paste0("Tract Number: ", cville_nri$NAME, "<br>",
                             "Ann. Freq.: ", round(cville_nri$RFLD_AFREQ, 2))
  ) %>% 
  addLegend("bottomright", pal = pal, values = cville_nri$RFLD_AFREQ, 
            title = "Riverine Flooding-#/year", opacity = 0.7)

Strong Wind

# SWND
pal <- colorNumeric("plasma", reverse = TRUE, domain = cville_nri$SWND_AFREQ) # viridis

leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons(data = cville_nri,
              fillColor = ~pal(SWND_AFREQ),
              weight = 1,
              opacity = 1,
              color = "white", 
              fillOpacity = 0.6,
              highlight = highlightOptions(
                weight = 2,
                fillOpacity = 0.8,
                bringToFront = T
              ),
              popup = paste0("Tract Number: ", cville_nri$NAME, "<br>",
                             "Ann. Freq.: ", round(cville_nri$SWND_AFREQ, 2))
  ) %>% 
  addLegend("bottomright", pal = pal, values = cville_nri$SWND_AFREQ, 
            title = "Strong Wind-#/year", opacity = 0.7)

Nota Bene

  • Coastal flooding not relevant for this region.
  • Most hazard overall ratings are very low or no ratings, except for drought; relative to larger national variation, these do not represent high risks.
  • Several hazard rates are dominated by regional effects, with little variation within th region.